Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Kiran K. S. Thingbaijam is active.

Publication


Featured researches published by Kiran K. S. Thingbaijam.


Seismological Research Letters | 2016

The Earthquake‐Source Inversion Validation (SIV) Project

P. Martin Mai; Danijel Schorlemmer; Morgan T. Page; Jean-Paul Ampuero; Kimiyuki Asano; Mathieu Causse; Susana Custódio; Wenyuan Fan; Gaetano Festa; Martin Galis; František Gallovič; Walter Imperatori; Martin Käser; Dmytro Malytskyy; Ryo Okuwaki; Fred F. Pollitz; Luca Passone; Hoby N. T. Razafindrakoto; Haruko Sekiguchi; Seok Goo Song; S. Somala; Kiran K. S. Thingbaijam; Cedric Twardzik; Martin van Driel; Jagdish Vyas; Rongjiang Wang; Yuji Yagi; Olaf Zielke

Finite-fault earthquake source inversions infer the (time-dependent) displacement on the rupture surface from geophysical data. The resulting earthquake source models document the complexity of the rupture process. However, multiple source models for the same earthquake, obtained by different research teams, often exhibit remarkable dissimilarities. To address the uncertainties in earthquake-source inversion methods and to understand strengths and weaknesses of the various approaches used, the Source Inversion Validation (SIV) project conducts a set of forward-modeling exercises and inversion benchmarks. In this article, we describe the SIV strategy, the initial benchmarks, and current SIV results. Furthermore, we apply statistical tools for quantitative waveform comparison and for investigating source-model (dis)similarities that enable us to rank the solutions, and to identify particularly promising source inversion approaches. All SIV exercises (with related data and descriptions) and statistical comparison tools are available via an online collaboration platform, and we encourage source modelers to use the SIV benchmarks for developing and testing new methods. We envision that the SIV efforts will lead to new developments for tackling the earthquake-source imaging problem.


Bulletin of the Seismological Society of America | 2016

Evidence for Truncated Exponential Probability Distribution of Earthquake Slip

Kiran K. S. Thingbaijam; P. Martin Mai

Earthquake ruptures comprise spatially varying slip on the fault surface, where slip represents the displacement discontinuity between the two sides of the rupture plane. In this study, we analyze the probability distribution of coseismic slip, which provides important information to better understand earthquake source physics. Although the probability distribution of slip is crucial for generating realistic rupture scenarios for simulation‐based seismic and tsunami‐hazard analysis, the statistical properties of earthquake slip have received limited attention so far. Here, we use the online database of earthquake source models (SRCMOD) to show that the probability distribution of slip follows the truncated exponential law. This law agrees with rupture‐specific physical constraints limiting the maximum possible slip on the fault, similar to physical constraints on maximum earthquake magnitudes. We show the parameters of the best‐fitting truncated exponential distribution scale with average coseismic slip. This scaling property reflects the control of the underlying stress distribution and fault strength on the rupture dimensions, which determines the average slip. Thus, the scale‐dependent behavior of slip heterogeneity is captured by the probability distribution of slip. We conclude that the truncated exponential law accurately quantifies coseismic slip distribution and therefore allows for more realistic modeling of rupture scenarios. Online Material: Figures showing scaling of slip area with seismic moment and Q – Q plots and tables listing earthquakes, rupture models, and fits of various distributions to the empirical probability distribution.


Pure and Applied Geophysics | 2017

Accounting for Fault Roughness in Pseudo-Dynamic Ground-Motion Simulations

P. Martin Mai; Martin Galis; Kiran K. S. Thingbaijam; Jagdish Vyas; Eric M. Dunham

Geological faults comprise large-scale segmentation and small-scale roughness. These multi-scale geometrical complexities determine the dynamics of the earthquake rupture process, and therefore affect the radiated seismic wavefield. In this study, we examine how different parameterizations of fault roughness lead to variability in the rupture evolution and the resulting near-fault ground motions. Rupture incoherence naturally induced by fault roughness generates high-frequency radiation that follows an ω−2 decay in displacement amplitude spectra. Because dynamic rupture simulations are computationally expensive, we test several kinematic source approximations designed to emulate the observed dynamic behavior. When simplifying the rough-fault geometry, we find that perturbations in local moment tensor orientation are important, while perturbations in local source location are not. Thus, a planar fault can be assumed if the local strike, dip, and rake are maintained. We observe that dynamic rake angle variations are anti-correlated with the local dip angles. Testing two parameterizations of dynamically consistent Yoffe-type source-time function, we show that the seismic wavefield of the approximated kinematic ruptures well reproduces the radiated seismic waves of the complete dynamic source process. This finding opens a new avenue for an improved pseudo-dynamic source characterization that captures the effects of fault roughness on earthquake rupture evolution. By including also the correlations between kinematic source parameters, we outline a new pseudo-dynamic rupture modeling approach for broadband ground-motion simulation.


Bulletin of the Seismological Society of America | 2017

New Empirical Earthquake Source‐Scaling Laws

Kiran K. S. Thingbaijam; P. Martin Mai; Katsuichiro Goda

We are thankful to all our colleagues for sharing their rupture models with the SRCMOD database. It is due to their generosity that the present and similar studies are possible. Careful and constructive comments by Shiro Hirano and two anonymous reviewers helped improve the article. The research presented in this article is supported by King Abdullah University of Science and Technology (KAUST) in Thuwal, Saudi Arabia, by Grants BAS/1/1339-01-1 and URF/1/2160-01-01.


Bulletin of the Seismological Society of America | 2017

Erratum to Evidence for Truncated Exponential Probability Distribution of Earthquake Slip

Kiran K. S. Thingbaijam; Paul Martin Mai

The scaling relationship between maximum slip u max and average slip u avg given by Thingbaijam and …


Marine Geology | 2014

Did a submarine landslide contribute to the 2011 Tohoku tsunami

David R. Tappin; Stephan T. Grilli; Jeffrey C. Harris; Robert J. Geller; Timothy Masterlark; James T. Kirby; Fengyan Shi; Gangfeng Ma; Kiran K. S. Thingbaijam; P. Martin Mai


Seismological Research Letters | 2014

SRCMOD: An Online Database of Finite‐Fault Rupture Models

P. Martin Mai; Kiran K. S. Thingbaijam


Seismological Research Letters | 2012

Probabilistic Seismic Hazard Assessment of India

Sankar Kumar Nath; Kiran K. S. Thingbaijam


Geophysical Journal International | 2015

Quantifying variability in earthquake rupture models using multidimensional scaling: application to the 2011 Tohoku earthquake

Hoby N. T. Razafindrakoto; P. Martin Mai; Marc G. Genton; Ling Zhang; Kiran K. S. Thingbaijam


Current Science | 2008

Disaster mitigation and management for West Bengal, India : An appraisal

Sankar Kumar Nath; Debasis Roy; Kiran K. S. Thingbaijam

Collaboration


Dive into the Kiran K. S. Thingbaijam's collaboration.

Top Co-Authors

Avatar

P. Martin Mai

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Sankar Kumar Nath

Indian Institute of Technology Kharagpur

View shared research outputs
Top Co-Authors

Avatar

Hoby N. T. Razafindrakoto

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Jagdish Vyas

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Ling Zhang

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Marc G. Genton

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Martin Galis

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Luca Passone

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Olaf Zielke

King Abdullah University of Science and Technology

View shared research outputs
Top Co-Authors

Avatar

Paul Martin Mai

King Abdullah University of Science and Technology

View shared research outputs
Researchain Logo
Decentralizing Knowledge